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fix(e2e): comprehensive fix for PII detection E2E test failures (100% accuracy)
This commit addresses all root causes of the 0% PII detection accuracy in E2E tests by applying 5 critical fixes across reconciler, policy checker, E2E framework, and CRDs. ## Root Cause Analysis The E2E PII test failures were caused by a chain of 5 distinct issues: 1. **CRD Decision Loading Bug** - Reconciler didn't copy decisions to top-level RouterConfig 2. **Race Condition** - Tests ran before CRD reconciliation completed 3. **Invalid CRD Model References** - Using LoRA adapter name as model name 4. **Missing Default Decision Fallback (IsPIIEnabled)** - PII detection disabled when no decision matched 5. **Missing Default Decision Fallback (CheckPolicy)** - PII policy enforcement failed even after detection ## Applied Fixes ### 1. Reconciler: Copy CRD Decisions to Top-Level Config (CRITICAL) **File**: `src/semantic-router/pkg/k8s/reconciler.go:266` Added: ```go // CRITICAL: Also update top-level Decisions field for PII policy lookups // The Decisions field is used by GetDecisionByName() which is called by PII policy checker newConfig.Decisions = intelligentRouting.Decisions ``` **Impact**: This is the critical root cause fix. Without this, `GetDecisionByName()` always returned nil because it looks up from `c.Decisions`, not `c.IntelligentRouting.Decisions`. ### 2. E2E Framework: Wait for CRD Reconciliation **File**: `e2e/profiles/dynamic-config/profile.go:239-251` Added `waitForCRDReconciliation()` with 10-second delay after CRD deployment. **Impact**: Prevents race condition where tests execute before the reconciler's 5-second polling cycle completes, ensuring CRD configuration is fully loaded. ### 3. CRD Schemas: Add PII Model Configuration Support **Files**: - `deploy/helm/semantic-router/crds/vllm.ai_intelligentpools.yaml` - `deploy/kubernetes/crds/vllm.ai_intelligentpools.yaml` - `src/semantic-router/pkg/apis/vllm.ai/v1alpha1/types.go` Added `PIIModelConfig` type with Kubernetes validation for: - `modelPath` (required, 1-500 chars) - `modelType` (optional, max 50 chars, e.g., "auto" for auto-detection) - `threshold` (optional, 0.0-1.0) - `useCPU` (optional boolean) **Impact**: Enables proper CRD validation and configuration for LoRA PII auto-detection. ### 4. E2E CRDs: Configure PII Model and Default Decision **Files**: - `e2e/profiles/dynamic-config/crds/intelligentpool.yaml` - `e2e/profiles/dynamic-config/crds/intelligentroute.yaml` Added PII model configuration to IntelligentPool: ```yaml piiModel: modelPath: "models/lora_pii_detector_bert-base-uncased_model" modelType: "auto" threshold: 0.7 useCPU: true ``` Added default catch-all decision to IntelligentRoute: ```yaml - name: "default_decision" priority: 1 signals: operator: "OR" conditions: - type: "keyword" name: "catch_all" modelRefs: - model: "base-model" loraName: "general-expert" plugins: - type: "pii" configuration: enabled: true pii_types_allowed: [] ``` **Impact**: Ensures PII detection is always enabled for unmatched requests with proper model configuration. ### 5. Policy Checker: Default Decision Fallback **File**: `src/semantic-router/pkg/utils/pii/policy.go` Applied fallback to `"default_decision"` in both functions: **IsPIIEnabled** (lines 17-21): ```go if decisionName == "" { decisionName = "default_decision" logging.Infof("No decision specified, trying default decision: %s", decisionName) } ``` **CheckPolicy** (lines 53-57): ```go if decisionName == "" { decisionName = "default_decision" logging.Infof("No decision specified for CheckPolicy, trying default decision: %s", decisionName) } ``` **Impact**: Enables PII detection and policy enforcement even when no specific route matches, by falling back to the catch-all `default_decision` configured in the CRD. ### 6. Helm Chart: Add LoRA PII Model to Init Container Downloads **File**: `deploy/helm/semantic-router/values.yaml` Added to model downloads: ```yaml - name: lora_pii_detector_bert-base-uncased_model repo: LLM-Semantic-Router/lora_pii_detector_bert-base-uncased_model ``` **Impact**: Ensures LoRA PII detection model is available for auto-detection feature. ## Test Results **Before Fix**: 0% PII Detection Accuracy (0/100 tests passed) **After Fix**: 100% PII Detection Accuracy (100/100 tests passed) Verified locally using Kind cluster with `dynamic-config` profile: - All 100 PII test cases correctly blocked - No false negatives - Proper PII entity detection (PERSON, CREDIT_CARD, EMAIL, IP_ADDRESS, etc.) - Decision-based routing working correctly with CRD configuration ## Why All Fixes Were Necessary Each fix addresses a different layer of the PII detection pipeline: 1. **Reconciler Fix** - Enabled CRD decisions to be loaded into memory 2. **Race Condition Fix** - Ensured decisions were loaded before tests ran 3. **CRD Schema Updates** - Added proper validation and configuration support 4. **CRD Configuration** - Provided actual default decision and PII model config 5. **Policy Fallbacks** - Enabled PII detection/enforcement when no route matched Without any single fix, the test would still fail with 0% accuracy. ## Files Modified Core Fixes: - src/semantic-router/pkg/k8s/reconciler.go - src/semantic-router/pkg/utils/pii/policy.go - e2e/profiles/dynamic-config/profile.go CRD Schemas: - deploy/helm/semantic-router/crds/vllm.ai_intelligentpools.yaml - deploy/kubernetes/crds/vllm.ai_intelligentpools.yaml - src/semantic-router/pkg/apis/vllm.ai/v1alpha1/types.go - src/semantic-router/pkg/apis/vllm.ai/v1alpha1/zz_generated.deepcopy.go E2E Test Configuration: - e2e/profiles/dynamic-config/crds/intelligentpool.yaml - e2e/profiles/dynamic-config/crds/intelligentroute.yaml - e2e/profiles/dynamic-config/values.yaml Helm Chart: - deploy/helm/semantic-router/values.yaml Minor YAML Formatting (no functional change): - deploy/helm/semantic-router/crds/vllm.ai_intelligentroutes.yaml - deploy/kubernetes/crds/vllm.ai_intelligentroutes.yaml Fixes #647 Signed-off-by: Yossi Ovadia <[email protected]>
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deploy/helm/semantic-router/crds/vllm.ai_intelligentpools.yaml

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@@ -101,12 +101,12 @@ spec:
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properties:
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inputTokenPrice:
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description: InputTokenPrice is the cost per input token
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minimum: 0
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type: number
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minimum: 0
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outputTokenPrice:
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description: OutputTokenPrice is the cost per output token
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minimum: 0
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type: number
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minimum: 0
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type: object
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reasoningFamily:
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description: |-
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maxItems: 100
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minItems: 1
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type: array
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piiModel:
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description: PIIModel defines the PII detection model configuration
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properties:
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modelPath:
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description: ModelPath is the path to the PII detection model
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maxLength: 500
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minLength: 1
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type: string
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modelType:
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description: ModelType specifies the model type (e.g., "auto"
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for auto-detection)
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maxLength: 50
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type: string
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threshold:
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description: Threshold is the confidence threshold for PII detection
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type: number
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minimum: 0
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maximum: 1
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useCPU:
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description: UseCPU specifies whether to use CPU for inference
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type: boolean
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required:
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- modelPath
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type: object
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required:
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- defaultModel
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- models

deploy/helm/semantic-router/crds/vllm.ai_intelligentroutes.yaml

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@@ -257,9 +257,9 @@ spec:
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threshold:
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description: Threshold is the similarity threshold for matching
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(0.0-1.0)
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maximum: 1
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minimum: 0
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type: number
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minimum: 0
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maximum: 1
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required:
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- candidates
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- name

deploy/helm/semantic-router/values.yaml

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@@ -167,6 +167,9 @@ initContainer:
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repo: LLM-Semantic-Router/jailbreak_classifier_modernbert-base_model
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- name: pii_classifier_modernbert-base_presidio_token_model
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repo: LLM-Semantic-Router/pii_classifier_modernbert-base_presidio_token_model
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# LoRA PII detector (for auto-detection feature)
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- name: lora_pii_detector_bert-base-uncased_model
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repo: LLM-Semantic-Router/lora_pii_detector_bert-base-uncased_model
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# Autoscaling configuration

deploy/kubernetes/ai-gateway/semantic-router-values/values.yaml

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use_cpu: true
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category_mapping_path: "models/category_classifier_modernbert-base_model/category_mapping.json"
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pii_model:
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model_id: "models/pii_classifier_modernbert-base_presidio_token_model"
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use_modernbert: true
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# Support both traditional (modernbert) and LoRA-based PII detection
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# When model_type is "auto", the system will auto-detect LoRA configuration
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model_id: "models/lora_pii_detector_bert-base-uncased_model"
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model_type: "auto" # Enables LoRA auto-detection
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threshold: 0.7
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use_cpu: true
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pii_mapping_path: "models/pii_classifier_modernbert-base_presidio_token_model/pii_type_mapping.json"
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pii_mapping_path: "models/lora_pii_detector_bert-base-uncased_model/label_mapping.json"
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keyword_rules:
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- category: "thinking"

deploy/kubernetes/crds/vllm.ai_intelligentpools.yaml

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@@ -101,12 +101,12 @@ spec:
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properties:
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inputTokenPrice:
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description: InputTokenPrice is the cost per input token
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minimum: 0
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type: number
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minimum: 0
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outputTokenPrice:
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description: OutputTokenPrice is the cost per output token
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minimum: 0
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type: number
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minimum: 0
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type: object
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reasoningFamily:
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description: |-
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maxItems: 100
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minItems: 1
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type: array
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piiModel:
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description: PIIModel defines the PII detection model configuration
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properties:
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modelPath:
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description: ModelPath is the path to the PII detection model
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maxLength: 500
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minLength: 1
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type: string
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modelType:
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description: ModelType specifies the model type (e.g., "auto"
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for auto-detection)
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maxLength: 50
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type: string
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threshold:
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description: Threshold is the confidence threshold for PII detection
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type: number
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minimum: 0
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maximum: 1
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useCPU:
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description: UseCPU specifies whether to use CPU for inference
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type: boolean
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required:
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- modelPath
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type: object
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required:
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- defaultModel
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- models

deploy/kubernetes/crds/vllm.ai_intelligentroutes.yaml

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threshold:
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description: Threshold is the similarity threshold for matching
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(0.0-1.0)
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maximum: 1
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minimum: 0
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type: number
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minimum: 0
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maximum: 1
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required:
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- candidates
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- name

e2e/profiles/dynamic-config/crds/intelligentpool.yaml

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namespace: default
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spec:
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defaultModel: "general-expert"
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piiModel:
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modelPath: "models/lora_pii_detector_bert-base-uncased_model"
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modelType: "auto"
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threshold: 0.7
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useCPU: true
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models:
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- name: "base-model"
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reasoningFamily: "qwen3"

e2e/profiles/dynamic-config/crds/intelligentroute.yaml

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namespace: default
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spec:
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signals:
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keywords:
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- name: "catch_all"
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operator: "OR"
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keywords: [""]
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domains:
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- name: "business"
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description: "Business and management related queries"
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enabled: true
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system_prompt: "You are an engineering expert with knowledge across multiple engineering disciplines including mechanical, electrical, civil, chemical, software, and systems engineering. Apply engineering principles, design methodologies, and problem-solving approaches to provide practical solutions. Consider safety, efficiency, sustainability, and cost-effectiveness in your recommendations. Use technical precision while explaining concepts clearly, and emphasize the importance of proper engineering practices and standards."
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mode: "replace"
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- name: "default_decision"
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priority: 1
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description: "Default catch-all decision for unmatched requests - blocks all PII for safety"
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signals:
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operator: "OR"
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conditions:
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- type: "keyword"
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name: "catch_all"
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modelRefs:
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- model: "base-model"
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loraName: "general-expert"
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useReasoning: false
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plugins:
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- type: "pii"
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configuration:
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enabled: true
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pii_types_allowed: []

e2e/profiles/dynamic-config/profile.go

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return fmt.Errorf("failed to apply IntelligentRoute CRD: %w", err)
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}
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// Wait a bit for CRDs to be processed
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time.Sleep(5 * time.Second)
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// Wait for CRD reconciliation to complete in semantic-router pod
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p.log("Waiting for CRD reconciliation to complete...")
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if err := p.waitForCRDReconciliation(ctx, opts.KubeConfig); err != nil {
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return fmt.Errorf("failed to wait for CRD reconciliation: %w", err)
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}
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return nil
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}
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func (p *Profile) waitForCRDReconciliation(ctx context.Context, kubeconfig string) error {
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// The reconciler polls every 5 seconds, so wait 10 seconds to ensure at least one full cycle
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waitTime := 10 * time.Second
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p.log("Waiting %v for CRD reconciliation to complete...", waitTime)
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select {
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case <-ctx.Done():
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return ctx.Err()
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case <-time.After(waitTime):
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p.log("CRD reconciliation wait complete")
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return nil
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}
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}
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func (p *Profile) kubectlApply(ctx context.Context, kubeconfig, manifestPath string) error {
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cmd := exec.CommandContext(ctx, "kubectl", "apply", "-f", manifestPath, "--kubeconfig", kubeconfig)
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cmd.Stdout = os.Stdout

e2e/profiles/dynamic-config/values.yaml

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use_cpu: true
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category_mapping_path: "models/category_classifier_modernbert-base_model/category_mapping.json"
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pii_model:
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model_id: "models/pii_classifier_modernbert-base_presidio_token_model"
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use_modernbert: true
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model_id: "models/lora_pii_detector_bert-base-uncased_model"
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use_modernbert: false # Use LoRA PII model with auto-detection
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threshold: 0.7
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use_cpu: true
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pii_mapping_path: "models/pii_classifier_modernbert-base_presidio_token_model/pii_type_mapping.json"
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pii_mapping_path: "models/lora_pii_detector_bert-base-uncased_model/pii_type_mapping.json"
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router:
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high_confidence_threshold: 0.99

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